Selection index for economically important traits in Boer crossbred goats using principal component analysis

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Animal Breeding

Background:

• Economic selection indices are optimal for genetic improvement but challenging in developing countries due to data limitations.
• Crossbred goats are important livestock, and efficient breeding strategies are crucial for their productivity.

Purpose of the Study:

• To construct alternative selection indices for crossbred goats.
• To explore relationships among economically important traits.
• To provide a viable alternative to economic selection indices in data-scarce environments.

Main Methods:

• Utilized a dataset of crossbred goat records including birth weight (BW), weaning weight (WW), weight gain (ADG), Kleiber ratio (KR), relative growth rate (RGR), growth efficiency (GE), and survival (RR).
• Employed single-trait animal models for genetic parameter estimation.
• Applied Principal Component Analysis (PCA) and cluster analysis to identify trait groupings and derive selection indices (Principal Component Scores - PCS).

Main Results:

• Two principal components (PCS1 and PCS2) explained 72.28% of the total genetic additive variance.
• PCS1 correlated with WW, ADG, KR, GE, and RGR, indicating its utility for improving growth-related traits.
• PCS2 correlated with BW and RR, suggesting its use for improving birth weight and survival.

Conclusions:

• Developed two principal component-based selection indices (PCS1 and PCS2) as practical alternatives to economic selection indices for crossbred goats.
• PCS1 aids in enhancing growth and efficiency traits, while PCS2 assists in improving birth weight and survival.
• The choice of index depends on specific breeding objectives, offering flexibility for genetic improvement programs.